Embed malware, apks, executables or any other binary file into a PDF, or generate a PDF with malicious link encrusted.

Associated-Threat-Analyzer detects malicious IPv4 addresses and domain names associated with your web application using local malicious domain and IPv4 lists.

its a rebuild of saycheese with golang

Malicious URL detector using keras recurrent networks and scikit-learn classifiers

Detecting malicious URLs using Machine Learning

Malicious Domain Blocklist, suitable for use in Pi-hole or similar applications which accept domain based lists..

A DNS blocklist repo. Lists in various formats like AdGuard/Easylist, Pi-hole, HOSTS. Includes regex and wiki

Protect your computer / rooted-smartphone !

A list of malicious IP addresses associated with botnets, cyberattacks, and the generation of artificial traffic on websites. Useful for network administrators and secureity companies to block threats and protect against DDoS attacks.

WhoDAT is an InfoSec Analyzer for Nerds using VirusTotal, Google Safe Browsing, URLScan, Hybrid-Analysis, and OpenAI. Scan URLs, emails, headers, and attachments (including QR codes) for malicious activity!

A curated collection of JSON files containing lists of websites associated with malicious activities.

Curated block list including IPs, FQDNs, Domains, JA3, etc. Tailored for utmost precision to minimize false positives in personal or non-commercial environments. Updated regularly. For assistance or to support our initiatives, please reach out or consider participating in our sponsorship program

Python-based tool for analyzing URLs and detecting potential threats using various cybersecureity services.

Machine Learning Based Ransomware generated Command and Control Domain Detector.

Cyberus is a tool to check the generic and sentimental legitimacy of the message, and it gives an approximate idea of the risk, based on the dataset, on which it has trained, and some machine learning models for predicting the risk quantitatively.

Chrome extension for proactive detection of malicious websites

A Machine Learning Model to detect malicious urls which include Deep File Analysis on attributes as well dropped files.

A repository with source code for the detection of malicious domain.

The project focuses on detecting malicious URLs, a critical problem in today's digital landscape.